Team Members: Lorenzo Lucena Maguire, Ruturaj A. Nanoti, Siddhant Mathur
In this project we performed a comparative analysis of vision based models, namely CNN, ConvMixer and MLP-Mixer for prediction of chess board states using
images of chess boards (dataset obtained from Kaggle) and FEN (string based notation for encoding chess
board positions) labels.
The report for the project can be accessed by clicking here.